Artificial Intelligence still beggars the imagination. You can try to trace the story of Westworld series to feel perception and fears related with implementation and development of this technology.

The fact is that technologies related to artificial intelligence and machine learning have been around us for several decades and we use them every day without even realizing it. Also companies are outdoing themselves in creating ideas how use AI to build competitive advantage.

Despite the fact that we all use the term artificial intelligence, its definition from the very beginning was hard to precise, and appearing new concepts does not make it easier. So what is the difference between Artificial Intelligence, Machine Learning and Deep Learning? Where can we meet AI in everyday life?

Artificial Intelligence

Artificial intelligence is a broad concept. In general, it aims to imitate human decision-making processes and perform complex tasks in a more human way than ever before. In AI definition you can find construction of machines and algorithms operating with characteristics of human intelligence for e.g.: having the ability to self-adapt to changing conditions. This is a much broader concept than Machine Learning. Behavioral algorithms, virtual agents or autonomously driven self-propelled vehicles are just a few examples of a current application of artificial intelligence.

AI can be divided into two categories:

Weak AI (also known as narrow AI) – focuses only on a narrow predefined task, is limited to its scope and does not go beyond

Strong AI (also known as general AI) – is a broader concept, in its scope it includes a system with comprehensive knowledge and cognitive abilities, in the assumption similar to human thinking.

Machine Learning

So what is Machine Learning? Machine Learning is a subset of artificial intelligence. Allows the algorithm to grow. The first definition was created by Artur Samuel, who defined the concept of ML in 1959:

“Field of study that gives computers the ability to learn without being explicitly programmed”.

By analysing huge amounts of data, the system is able to grow and learn how to perform a specific task. Based on an independent analysis, using mathematical algorithms to search data and find models, it is able to predict the result or make a decision. So all machine learning is artificial intelligence, but not all AI is machine learning.

However, machine learning, despite the fact that it is able to develop, when it hasn’t enough data and then faces the necessity of making decisions, human intervention is needed. What if we want to go further?